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This work investigates the influence of rheological contrasts on the nucleation and behavior of strike-slip faults. To achieve this, we have carried out a series of brittle-viscous strike-slip shear analogue models, using quartz sand and microbeads as granular materials with different internal friction and cohesion values. Particle Imaging Velocimetry (PIV) was applied to time-series of surface images to calculate incremental and cumulative strains. Understanding how strike-slip faults nucleate and interact in the heterogeneous upper crust is relevant in seismic hazard analysis and geothermal and hydrocarbon exploration. To reproduce the heterogeneity of the upper crust, three sets of experiments we performed: 1) upper layer composed either of quartz sand or microbeads; 2) upper layer with a vertical contrast i.e., quartz sand surrounded by microbeads and vice-versa; and 3) same set-up as in the previous set but changing the orientation of the vertical contrast. Our study shows that the introduction of an upper crustal vertical contrast influences the behavior and evolution of strike-slip faults. The models containing a vertical contrast were more complex and induced a compartmentalization of the model. The initial fault strike is related to the material's properties. However, this initial strike changes when faults crosscut the materials with less internal friction angle clockwise, and anticlockwise when the contrast has higher internal friction angle. Areas containing materials with less internal friction angle take longer to localized the deformation, but they show a greater number of faults. The biggest increase in the number of synthetic and antithetic faults occurs with the introduction of vertical contrast. These results were compared with the intraplate fault systems of the NW Iberian Peninsula, focusing on the Penacova-Régua-Verin and Manteigas-Vilariça-Bragança fault systems. They are major left-lateral faults that cross-cut lithologies characterized by vertical rheological contrasts, with deformation patterns similar to those observed in our analogue models. [ABSTRACT FROM AUTHOR]

Regeneration after landslides is how an ecosystem recovers itself following a landslide event. Natural systems can recover and regenerate over time. The main objective of the current work is to identify and characterise the regeneration pattern after a great landslide event in 2013 in the Guerrero state (Mexico) using remote sensing, geographic information system (GIS), and machine learning techniques. Remarkably, the authors consider normalised difference vegetation index (NDVI) as a proxy of part of this "regeneration" in the present work. A first methodology attempt presented here was to monitor and characterise the "regeneration" after severe landslide events. First, the authors calculated and identified the (1) losses, (2) speed and (3) recovery time through a continuous change detection and classification algorithm (CCDC) in Google Earth Engine (GEE) from a NDVI-Landsat time series (from 1984 to 2021). Second, these three factors were introduced as variables in a not supervised machine-learning model to get 5 clusters that characterise the different regeneration patterns followed from 2013 to 2021 in the landslide zones. Finally, we studied 16 variables like elevation, slope, or soil pH. The authors included those variables in a supervised machine learning classification to find the most important main drivers related to the NDVI regeneration of the landslide areas. The results showed that the cluster called Group 0 had a low loss of NDVI value, speed and medium recovery time. Group 1 showed a medium–high loss, high speed and low recovery time. Group 2 reached a high loss, a low speed, and an increased recovery time. Group 3 with a medium loss, a medium speed, and a low recovery time. Finally, Group 4 with a high loss of NDVI, a medium speed, and a medium recovery time. Distance to the edge of the landslide, precipitation, land cover type and lithology are highlighted as the main drivers in landslide regeneration. [ABSTRACT FROM AUTHOR]

Earthquakes with magnitudes greater than 4.5–5 induce massive rockfalls close to the fault rupture zone. Driven by seismic shaking, the blocks collapse through the hillslope, which yields a fresh surface that is unbeatable for new lichen colonization. The lichenometric technique involves dating lichens developed on the surfaces of rockfall blocks induced by earthquakes. This study is focused on Cejo de Cano (Lorca, Spain), which is an earthquake-prone landslide scarp, as shown after the 2011 Lorca shaking (Mw 5.2). After this event, the possibility that the rocky volume at the foot of its slope could have a seismic origin started to be considered. In this research, lichenometry is used to date lichens on rock surfaces and test a possible correlation with the cataloged historical earthquakes. This research is important because of the large number of rockfall earthquakes found at this site by applying lichenometry compared to other studies in the literature. This technique allows us to extend the regional seismic catalog because the oldest lichens are older than the documented catalog of historical earthquakes. An oriented rockfall pattern that correlates with the location of epicenters is observed. In addition, the parallel and oblique previous fracturing of Cejo de Cano makes this scarp a suitable place to test whether the fracturing direction of the scarp could control a greater volume of rockfalls. This research opens up a new field of study to evaluate this correlation in larger areas. [ABSTRACT FROM AUTHOR]

The unprecedented and long-lasting seismicity of Triacastela (over 25 years) attracted the interest of the research community on this stable continental region (SCR), particularly after the anomalously high 5.1 and 4.9 Mw earthquakes compared to the regional standards. The high rainfall and tide rates of this region compared to the rest of the Iberian Peninsula, in addition to the recognized existence of thermal springs and crustal fluids, motivated us to test these sources of hydroseismicity as a potential trigger mechanism for the observed seismicity in Triacastela. Based on network upgrades, we have gathered the seismic catalog in two periods for analysis (before and after year 2002). Before 2002, neither a diffusion-type earthquake migration nor any significant statistical correlation between the seismicity rates and rainfall or tides is found. After 2002, some clusters migrate to the south, suggesting the presence of fluid migration during earthquake swarms, but no diffusion-type migration is observed on longer time scales. Furthermore, we find correlation coefficients close to zero, indicating that rainfall and tides can be excluded as driving mechanisms. However, the seismic upward migration, a high b-value (1.2), and a low aftershock-productivity parameter (α = 0.9) observed in this period support the hypothesis of upward fluid migration through fracture zones. The presence of Mantellic helium-3 along the seismogenic faults and the increase of geochemical precursors in the groundwater previously to 1995 and 1997 mainshocks further support deep fluids as a source for the observed induced fluid migration seismicity in Triacastela. [ABSTRACT FROM AUTHOR]

The management of a UNESCO Global Geopark (UGGp) requires a vast wealth of miscellaneous scientific knowledge that can be successfully organised using a Geographical Information System (GIS). This paper presents a pragmatic GIS database to assist in the suitable governance of the Courel Mountains UGGp (2017) in Northwest Spain. The database is structured in 66 coverages compiled from public sources and previous works or produced through traditional mapping (combining fieldwork and photointerpretation) and GIS tools. The acquired data was later homogenised and validated by a multidisciplinary team and archived in independent coverages. Forty thematic maps illustrate the broad range of cartographic information included in the GIS database. Among them, 25 basic maps provide an overview of the UGGp and 15 new maps focus on crosscutting and technical issues. All maps illustrate the huge potential of GIS to create new resources combining coverages and adapting the legend according to their purpose and audience. The database facilitates the suitable publishing of consistent outputs (e.g., brochures, books, panels, webpages, web serves), as well as the elaboration of technical data to assist the park management. The database furnishes information on the design of education actions, touristic routes, activities and Geopark facilities. The GIS database is also a supportive tool for scientific research and provides the necessary knowledge to conduct geoconservation actions based on land use, geological hazards and the occurrence of natural and cultural heritages. Altogether, the GIS database constitutes a powerful instrument for policy-making, facilitating the identification and evaluation of alternative strategy plans. [ABSTRACT FROM AUTHOR]

The Cabuérniga Fault System (CFS) extends for 150 km in E-W trend along the northern divide of the Cantabrian Mountains, near the Cantabrian Sea. This fault system was reactivated several times since the Paleozoic, and displays hydrothermal activity nowadays. We present here a detailed geological map of the whole CFS and six cross-sections distributed along strike, which allowed us to unravel the kinematic history of the individual fault segments comprising the CFS. The current CFS geometry mainly results from the reactivation of E-W Variscan thrusts and NW-SE Late-Variscan strike-slip faults during the Alpine Cycle. Reactivation took place in relation to both Permian and Mesozoic pre-orogenic extension and subsequent Cenozoic shortening. The eastern end of the CFS corresponds to a N-S structure arriving at the Cantabrian coast, while the western edge connects with the E-W trending Llanera fault, leading to an Alpine fault system extending 220 km. [ABSTRACT FROM AUTHOR]

The information and seismic parameters gained from pre-instrumental earthquakes are essential to improve the seismic catalogs and hazard studies. The earthquake damage (ED) that affected architectonic elements during earthquakes (e.g. fallen walls, conjugated fractures in walls, dropped keystones in arches), and when this earthquake damage is orientated (EDO), can be used to infer seismic parameters of pre-instrumental earthquakes such as epicenter location, seismogenic source or ground motion. However, there is not a common methodology to measure this orientation damage. For example, tilting and fallen walls are some of the most used elements to infer the horizontal ground motion in non-instrumental earthquakes. Nevertheless, according to the shape of the architectonic element (a wall in this case), it has only two degrees of freedom to fall, and therefore, its azimuth does not necessarily fit with the ground motion pulse orientation. In this work, a review of the earthquake damage (ED) and effects described in pre-instrumental earthquakes is carried out. A method is also proposed, considering not only the frequency of damage orientations but also considering the uncertainty angle of each element to be damage. The ED has been classified into five groups according to the angle of uncertainty to record the pulse orientation. This method has been checked taking advantage of recent earthquakes with a good instrumental record of the ground motion pulse, and also tested modeling different scenarios with different pulse orientations. This method, that takes into account the uncertainty angles, is a reliable method to calculate the EDO and back-calculate the ground motion pulse orientation in pre-instrumental earthquakes in absence of more accurate modern instrumental records. This method can also be useful for seismic risk assessment and restoration and protection of historical heritage. [ABSTRACT FROM AUTHOR]

We report the results of a multidisciplinary study of the early Permian (Artinskian–Kungurian) Sotres Formation of northern Spain integrating sedimentology, palaeosols, mineralogy, stable isotopes, palynology, ichnology and tectonics. This continental unit was deposited in the near-equatorial Peri-Tethyan Cantabrian Basin. Having developed in the middle of the Variscan fold belt, it is preserved within the present-day Cantabrian Mountains. Three subunits are recognised in the Sotres Formation based on tectono-stratigraphic and sedimentological data: a lower alluvial subunit, a middle carbonate lacustrine subunit, and an upper palustrine subunit. Multidisciplinary results reveal an upward change in climate from humid-subhumid conditions at the base of the formation (Artinskian) to semi-arid and arid conditions at the top of the formation (Kungurian), which may reflect global deglaciation near the end of the Late Paleozoic Ice Age and a probable northward migration of the Intertropical Convergence Zone. This general upward warming/drying climate trend was interrupted by a short-lived interval of monsoon conditions in mid-Kungurian times, which may have coincided with a pulse of global cooling. Our findings are in agreement with the climate trends reported for other central Pangaean basins. Rising CO2 levels may have been a driving factor for climate transition during this time interval. However, in our study area, which lies within the active central Variscan orogenic belt, tectonic conditions must have also played a role in driving climate change. [ABSTRACT FROM AUTHOR]

Landslides are recognized as high-impact natural hazards in different regions around the world; therefore, they are extensively researched by experts. Landslide inventories are essential to identify areas that are likely to be affected in the future, thereby enabling interventions to prevent loss of life. Today, through combined approaches, such as remote sensing and machine learning techniques, it is possible to apply algorithms that use data derived from satellite images to produce landslide inventories. This work presents the performance of five machine learning methods—k-nearest neighbor (KNN), stochastic gradient descendent (SGD), support vector machine radial basis function (SVM RBF Kernel), support vector machine (SVM linear kernel), and AdaBoost—in landslide detection in a zone of the state of Guerrero in southern Mexico, using continuous change maps and primary landslide factors, such as slope angle, terrain orientation (aspect), and lithology, as inputs. The models were trained with 2/3 of ground truth samples of 671 slidden/non-slidden polygons. The obtained inventory maps were evaluated with the remaining 1/3 of ground truth samples by generating a confusion matrix and applying the Kappa concordance coefficient, accuracy, precision, recall, and F1 score as evaluation metrics, as well as omission and commission errors. According to the results, the AdaBoost classifier reached greater spatial and statistical coherence than the other implemented methods. The best input layer combination for detection was the continuous change maps obtained by the linear regression and image differencing detection methods, together with the slope angle, aspect, and lithology conditioning factors. [ABSTRACT FROM AUTHOR]